Quantum entanglement for magnetometry

Quantum metrology promises enhanced precision by harnessing entanglement and quantum algorithms. Yet, realizing such gains on current noisy quantum hardware remains a significant challenge. Here, we investigate quantum-enhanced magnetometry using phase estimation algorithms on superconducting quantum processors the IQM Garnet and Rigetti Ankaa-3. We experimentally compare the performance of different entangled, parallel and combined sensing strategies. While the entangled states should provide improvements in sensitivity in ideal conditions, we find that their advantage is less in practice on currently available systems. Instead, partitioning qubits into smaller entangled subsets and operating them in parallel achieves near-optimal sensitivity. We derive a general expression for magnetometric precision as a function of total qubit number and subset entanglement size, based on the attenuation of the system, identifying optimal configurations under realistic noise constraints.